NBA Power Rankings for the 2012-13 Season volume #1

And in typical editor fashion, I’ll be skipping to dessert first. Here are Arturo’s power rankings for the NBA as things currently stand (through 11-28-2012 games, excluding the Clippers vs. Minnesota) Don’t worry, he explains his methods in the post!

Arturo’s Awesome 2013 NBA Power Rankings as of 11-28-2012

*Playoff teams in bold.

Rank

Team

Expected Wins

1

Memphis Grizzlies

64

2

New York Knicks

63

3

Oklahoma City Thunder

63

4

San Antonio Spurs

60

5

Miami Heat

58

6

Los Angeles Clippers

57

7

Denver Nuggets

52

8

Brooklyn Nets

50

9

Los Angeles Lakers

50

10

Atlanta Hawks

47

11

Houston Rockets

46

12

Utah Jazz

43

13

Golden State Warriors

43

14

Chicago Bulls

42

15

Milwaukee Bucks

39

16

Indiana Pacers

38

17

Boston Celtics

38

18

Philadelphia 76ers

34

19

Minnesota Timberwolves

34

20

Detroit Pistons

34

21

Dallas Mavericks

32

22

Portland Trail Blazers

31

23

New Orleans Hornets

30

24

Toronto Raptors

29

25

Sacramento Kings

29

26

Cleveland Cavaliers

28

27

Orlando Magic

28

28

Phoenix Suns

26

29

Charlotte Bobcats

22

30

Washington Wizards

18

“It is not unscientific to make a guess, although many people who are not in science think it is.”— The Character of Physical Law, Richard P. Feynman

The law of large numbers (LLN) describes the result of performing the same experiment a large number of times. It’s a simple enough theorem, the average of results obtained from a large sample (or number of trials) will get closer and closer to the real value of something the larger the sample. Conversely, the error (or more accurately the possibility of it) gets larger and larger the smaller the sample.

What does this mean for us?

Next on ESPN! (image courtesy of xkcd.com)

Jumping to conclusion at this point in the season is premature. We simply need more data to start crowning people. The schedule is unbalanced, players are out and all sorts of other random variables are skewing the results.

We do however possess enough know how to reduce some of this noise to maximize what we can actually learn from the current sample. And that is precisely what I’ve been doing with my time.

It may be a small sample size but if we are careful we can actually derive some actual meaning from it. At least enough to make a guess.

The NBA regular season schedule is rigged for (hello Denver and Utah) and against (hello Spurs and Lakers) certain teams. It’s also not perfectly balanced. There are varying degrees of difficulty during the season for teams. We will account for this both in the power rankings and in the schedule.

The schedule so far looks like this:

The Clippers, Heat ,Hornets have faced the roughest schedule. The Twolves, Bulls and Jazz have faced the easiest schedule. This should start approaching historical patterns as the season progresses.

Point Margin per Game: Pts scored by team -Pts scored by opponent divided by games played

Home court Point Margin per Game: Point Margin per game due to the schedule and homecourt advantage.

Adjusted Point Margin per Game: Point Margin per Game -Home court Point Margin per Game. Schedule independent point margin (neutral site at sea level)

Adjusted Opponent Point Margin: The average Point Margin per Game of a teams opponents.

Real Point Margin (RPM): Point Margin per Game -Home court Point Margin per Game +Adjusted Opponent Point Margin. Expected Point Margin at a neutral site against perfectly average opposition. This is the Number I use to rank.

Neutral Site Win % : A win projection using the real point margin and the relationship between point margin and win% ( RPM/31 + .500 is a quick shorthand but not quite right, don’t worry I’m in the process of writing this up)

Keep in mind that this is a guess (a very scientific one but still a guess) at the relative strengths of teams based on the data of the season to date. We still need to account for injuries and incorporate what we know of player historical performance. We will address this in a, say it with me, future post.

A few notes:

The Eastern Conference looks looked in as predicted as a two team race between the Knicks and Heat who come in at #2 and #5 in the power ranking. Brooklyn (surprisingly) and Atlanta (not surprisingly) round out the top 4 in the east at #7 and #11 overall.

The next group in the east has injury depleted Chicago and roster turnover happy Boston. Both this teams should improve later in the year once they field their missing players (Rose, Bradley) and figure out their rotations.

The West is very,very strong with Memphis as our overall number #1 seed and OKC, San Antonio nipping their heels at #3 and #4. Memphis has benefited from some improved shot selection as well as generally improving play from their core group (I believe these are not separate things). Memphis went from 5th last year to 26th this year so far in % of shots taken from 3-23 feet (sh** shots) and from 28th to 6th in % of shots from threes. OKC and San Antonio are who they are.

The rest of the west features the Clippers and Denver who have both been penalized by the schedule and the Lakers who’ve we discussed extensively at #6,#9 and #8 respectively.

Let’s adjust for the expected season schedule now and project win totals for the rest of the year.

And that’s real pretty but let’s summarize and close.

The big surprise in the East so far is Brooklyn which I’d credit completely to Brook Lopez playing like an average player. Given his age, I’d be optimistic as a Nets fan. If Deron can get his groove back, they could be a contender.

The Knicks are slight surprise but I’d expect age to bring them back down to our predicted range. Still enough to have Melo in that MVP discussion.

As for disappointments, we have the Wizards, Raptors and Sixers which are all injury driven and except for the Raptors, expected.

The West’s big surprise is the number one team in our rank the Grizzlies. As I said, age progression and supremely improved shot selection. I’d be optimistic but wary of Heroball if I were a Grizzlies fan. I do expect them to come down simply because the west is killer.

OKC, San Antonio and the Clipps are all riding high but again I expect this to adjust down simply because of the strength of the conference.

Houston is very intriguing given their youth. This is looking to very possibly be a very good team for a very long time.

Minnesota and the Hornets are very much underperforming but this is injury driven and 100% expected. These teams will be better.

The craziest part of this season so far is that the 2013 NBA finals could feature a Jailblazer reunion.

Ball don’t lie

That combined with the fact that Melo is passing up contested shots to pass to his open teammates and Sheed showed up in shape and is playing hard means Jason Kidd is definitely a witch.

With respect to Brooklyn, there have been two other factors that I think have significantly contributed to their unexpected success. Perhaps even more surprising than Lopez playing like an average center – which I do not find all that surprising, since he was an average center his first two years in the league – is that Andray Blatche is playing above average, which he’s never done before. At 16 MPG, that’s a significant boost in production. The other thing is Reggie Evans, who is playing even better than his normal awesome self, AND who is getting much more minutes than he’s usually received previously (kudos to Avery Johnson for seeing how well he’s played). Those two things have led Brooklyn’s bench to be extremely productive (something we saw again last night against the Celtics in Boston, when Brooklyn’s bench absolutely killed Boston’s awful bench).

If you’re going to project season wins you should probably take current wins as a given and then use your projected win percent for future games only. So Charlotte for instance will do significantly better.

Fred,
I thought about that and initially did it that way but I ended up projecting Point Margin for the season based on current performance and expected schedule (which I should actually calculate and not estimate). Once I have point Margin, I assume that the central limit theorem holds and teams regress to the mean. It means I expect Charlotte to crash hard based on their point margin.

Some points:
– Since 1984-85 (I was too lazy to look further), only once has 4 or more teams produced 60 or more wins (97-98) in the same season.
– Your east standings has only 5 above .500 teams. Five!

I’m hearing a lot about how Melo has somehow drastically changes this season, passing up open shots, taking better ones, etc. etc. Is this really true though, or are most people just ASSUMING he’s doing better because the Knicks have played so well, when in fact the credit should go to Kidd and others?

I know Melo’s played better than last year, but last year was a bit of an aberration for him: his TS% was 52.5%, when it usually hovers closer to the 55% mark. Right now Melo’s sitting at 57.3%, which would be a career high, but not absurdly higher than what he’s done in ’06, ’08, or even ’10 (and, to be quite frank, I’ll be shocked if he keeps up a 43% accuracy rate on threes for the entire season). But apart from this, Melo’s assists are actually significantly LOWER than his career average this season; they’re actually at a career low! He’s rebounding well, but he’s always rebounded fairly well, and that’s not too big of a shock. His turnovers are above his career average, his blocks are normal, and his steals are lower. His Wins Produces per 48 are above his career average, but due to the drop in assists are BELOW what he managed last year and the year before.

I haven’t really watched Knicks games, so maybe Carmelo has changed a bit but the stats just aren’t showing it. But as far as I can tell, this monumental Carmelo change seems to just be a storyline that’s coming up because the Knicks are winning, mostly due to Kidd/Chandler/Smith. Am I incorrect in this assumption?

Regarding Melo, according to NBA Geek, Melo is a below average player this year so far (ex last night’s game) – he has a WP48 of .095. That’s above his career average, but still. Also, I wonder how much of it is due to him actually playing PF but being compared with (i.e., having the positional adjustment of) a SF. If we classified Melo as a PF this year – which is where he has played the majority of his minutes – how would his WP48 look?

NBA geek allows you to do just that! Putting him in as a PF drops his WP48 to an abysmal .025, changing him from borderline average to decidedly bad. I’m actually surprised his WP48 is so bad this year given the increase in shooting efficiency; I’m certainly not anywhere near chanting “Melo for MVP!”, but still…

Arturo, Carmelo seems to be playing “great”, but that isn’t reflected in his WP. Why is that? His shooting percentage is a blistering 58 TS%, and he’s averaging nearly 27 points per game. His rebounding numbers stand at 7.2 per game, which aren’t amazing, but are certainly solid. It just seems that this type of player shouldn’t be ” a below average player” in terms of WP.

I think Arturo was close when he said that Jason Kidd is a witch. I actually think it is more accurate that he is a Jedi Master. He will keep playing not just for years to come but decades to come and still contribute. He is going to be the Yoda of the NBA, older than anyone could possibly guess and more skilled than anyone would possibly believe.

Remember Kidd was playing serious minutes and, for a good period of time, putting up a WP of 0.600 or so. Couple that with JR’s shooting during that period that got him a 0.400 WP, add Chandler, and really the team couldn’t lose.

For what it is worth, I agree with Bush above that you should have used current wins as a given. Yes, one can expect regression to the mean, but after events have happened, if you include those events in your data, then the mean has shifted. Charlotte will come back to earth, but they aren’t due to come crashing back harder because they got a lot of earlier wins. Those coins have been flipped and the fact that they all came up heads doesn’t mean there are extra tails stored up in future flips.

Denver is a bit of a disappointment of sorts — 8-9 and arguably the most bipolar team in the league (lose 3, win 4, lose 3, win 4, lose 3). D rating now lower than last year (106.6 compared to 106.2 last year), although to be fair Denver just got a taste of Showtime 3.0 with D’Antoni last night.

Not sure they’re a 50 win team (Corey Brewer? Really?) but I also don’t see the same level of stat dominance from Iguodala (not that I’ve ever considered him great as an alpha/lead player given his lack of desire to take/make big shots) that there has been in years past.

This makes, what, four straight seasons the wages of wins has significantly underestimated the grizzlies, if we make the not too bold assumption that 45 wins now looks unlikely. And I’m not sure “it’s because they’re taking less midrange shots” is the get out of jail free card you seem to suggest it is, given that open threes for good shooters, and good shots near the rim aren’t some kind of free resource…

Presumably there’s something on the team that’s just not being picked up in the sorts of box score model that are being used here.

Christina,
You can bug Arturo on specifics for this year. I will say that Marc Gasol and Zach Randolph just love making things difficult. At their best they’re a front court that is top of the the league. They can also be average. Not knowing which will show up can make life difficult.

Christina,
I was actually riding the Grizzlies in the 2010-11 Season (I picked them to beat the Spurs in Round 1 and was calling them out as a dark horse a the all star break). I also called to lose to the clips based on their numbers.

You are making a huge assumption. The data seems to suggest that up to that moving to 25% to 35% from 3Pt range as a percent of attempts it is a free resource. Memphis went from 16% from three at a 49% EFG and 101.6 pts per 100 poss(2011-12) to 20% from three 56% efg% and 105 pts per 100 poss (so far). Their shit shot % went up (i’m guessing from taking more open shots) and their % at the rim went down( I actually think this goes up). So without changing personnel a change in offense leads to an increase in efficiency.

hmm, was just thinking esp re:upsets with Knicks; are there specific stats (ie. Pace, o efficiency, d efficiency, etc) that earmarks certain styles of team play that are more or less effective than certain other styles? And would this be useful in weighting teams regarding win%?

[…] Keeping that in mind, let’s take a look at each season in detail and set the stage. For this I broke out my full model and simulated out the 1972, 2008 and the current season accounting for opponents, schedule and altitude using all the tools I typically use for the power rankings . […]